Closing the Loop: Applying Self-Driving Labs to the Right Materials Problems

Abstract:

Clean energy technologies are notoriously slow to commercialize because discovering and optimizing new materials for applications typically takes over a decade. To accelerate the discovery of thin-film materials, we have developed a self-driving laboratory that combines versatile film deposition and characterization capabilities with automated data analysis and optimization algorithms to enable the autonomous execution of thin-film material discovery campaigns. Here, we provide an overview of the workflow of our self-driving lab, as well as insight into the consequences of experimental non-idealities on optimization performance.